Pork Quality Genetic Improvement Strategies

Dr Chunyan Zhang, Geneticist, Genesus Inc.

For a pig breeding company, the ultimate goal is to provide pigs with the genetic potential to:

improve consumers` overall acceptance and eating experience (pork quality);
maximize producers` profit.

Pork quality is mostly linked with consumer sensory measurements including taste, juiciness, flavour, tenderness and overall acceptance. However, direct genetic improvement of these traits is usually slow and costly (mainly consumer taste panels) so limited amounts of data are available.

Intramuscular fat percentage (IMF) is considered a good indicator of many sensory traits, such as juiciness, flavour and overall acceptance (De Vol et al., 1988, Ngapo et al., 2013; Ishii et al., 2018). Pork with higher IMF has higher juiciness and is preferred by consumers’ (Ngapo et al., 2013; Lei et al., 2018). Marbling score is visually assessed by trained personnel and is a predictor of IMF, plus it has a positive and moderate to high genetic correlation (0.37-0.55) (Maignel et al., 2010; Miar et al., 2014; Willson et al., 2020) with IMF.

Compared to sensory measurements, marbling score and ultrasound IMF (measured on live animals by ultrasound scanning) are easier to collect and have moderate to high heritability (0.31-0.62) (Solanes et al., 2009; Gjerlaug-Enger et al., 2010; Ishii et al., 2018; Willson et al., 2020; Gao et al., 2021). Therefore, they can be used for selection to improve pork quality.

Historically, many pig breeding companies and pork industries have focused on reducing carcass backfat depth to increase carcass lean yield. Unfortunately, this reduction in backfat depth also results in a reduction in marbling given the positive but unfavourable genetic correlation between backfat depth and marbling (0.30-0.64) (Solanes et al., 2009; Miar et al., 2014; Willson et al., 2020). As a consequence, long-term selection focused on improving lean yield, with no consideration for marbling will negatively impact marbling and thus pork quality. However, the correlation between marbling and backfat depth is less than 1, so there is an opportunity to identify and select animals having less backfat and more marbling.

Genesus has conducted a carcass and pork quality program since 1998. We continue our efforts to improve pork quality along with producer profit by integrating the advanced knowledge and technologies in several areas as discussed below.

1) Improve both marbling and lean yield selection strategy

Given the unfavorable genetic correlation (0.30-0.64) between marbling and backfat depth, we put both traits in the selection index and give optimal selection emphasis. In this way, we select pigs having genetic ability for both higher marbling and lower backfat depth, thus “breaking” the unfavourable correlation. In mid-2017, marbling was included directly in the Duroc selection index. The genetic trends for these two traits are shown in the figure below. It clearly demonstrates that, in the 2018 to 2020 period, when both traits were included in the selection index and appropriately emphasised, the genetic trend for marbling increased while the backfat depth has decreased. In this way, we genetically improve both pork quality and lean yield.

2) Make use of genomic information

It is well known that including genomic information benefits genetic improvement, especially for the traits that cannot be directly measured on the selection candidates. Genesus has invested heavily in genomic selection research and utilises a custom SNP (single nucleotide polymorphism, a kind of genetic marker) chip with > 60K SNPs including many associated with pork quality. This SNP chip was fully implemented in genomic selection in 2018. The specific SNP chip continues to be updated though Genesus R&D efforts.

3) Carcass and pork quality program

In 1998, a purebred nucleus population program was implemented including on-farm ultrasound and in-plant carcass and pork quality data collection. The database has over 20,000 animals each recorded for over 60 pieces of information. In addition, we collect these data on full Genesus commercial (Duroc sires x Y-L dams) pigs through different R&D projects. We also have more than 5000 animals with carcass and pork quality data and genotypes. This continually growing phenotypic and genomic databases are the foundation for continued genetic improvement in carcass and pork quality.

4) Multiple trait evaluation models

Two main strategies are implemented in our multiple trait evaluation model. Firstly, we utilise indicator traits for carcass backfat depth, marbling and carcass loin depth, namely ultrasound backfat depth, ultrasound IMF and ultrasound loin depth, respectively. Indicator traits are those which are under genetic control and have moderate to high genetic correlations with the economic traits of interest (carcass backfat depth, marbling score and carcass loin depth). This enables us to directly measure the indicator traits on all selection candidates at the end of the grow-finish period. Secondly, we include genetic correlations among the carcass and pork quality traits, namely hot carcass weight, carcass loin depth, carcass fat depth, marbling, loin color and 24hr pH. Multiple trait evaluation models improve the accuracy of the estimated breeding values and consequently increase the genetic improvement rate for carcass and pork quality traits.

As a global pig breeding company, Genesus is focused on providing breeding stock with the genetic ability to provide the consumer with a superior eating experience while maximising profit for pork producers. Our continued investment in these important areas clearly demonstrate our dedication to our customers and the global pork industry.

References

De Vol DL et al., 1988. J Anim Sci. 66 (2): 385-395
Gao et al., 2021. Front Genet. 17 March
Gjerlaug-Enger et al., 2010. Animal. 4,11: 1832-1843
Ishii et al., 2018. Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Species - Porcine 1, 408
Lei et al., 2018. Advances in Pork Production, 29, Abstract #15
Maignel et al., 2010. Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Species breeding: Pig breeding - Lecture Sessions, 0668
Miar et al., 2014. J Anim Sci. 92:2869-2884
Miar et al., 2014. Plos One 9(10): e110105
Ngapo et al., 2013. Food Research International. 51, 985-991
Solanes et al., 2009. Livestock Science. 123,1:63-69
Willson et al., 2020. Animals. 10, 779

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